Abstracts – Browse Results
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Al-Zarrad, M A (2018) Multi-criteria decision-making model to improve linear repetitive projects time-cost trade-off in uncertain environment, Unpublished PhD Thesis, , University of Alabama.
Awolusi, I G (2017) Active construction safety leading indicator data collection and evaluation, Unpublished PhD Thesis, , University of Alabama.
Chau, A D (2018) Conceptual cost estimation decision support system in university construction projects, Unpublished PhD Thesis, , University of Alabama.
Egan, C M (1989) An evaluation of the effectiveness of the Mankato State university construction management program, Unpublished PhD Thesis, , University of Alabama.
Giron Matute, W A (2018) Sustainability analysis for construction companies under the LEED code, Unpublished PhD Thesis, , University of Alabama.
Harbin, K B (2020) A decision analysis tool for building renovations regarding adaptive reuse, Unpublished PhD Thesis, , The University of Alabama.
Hatamleh, M T (2020) Enhancing the management proficiencies in developing countries: The impact of project risk management within a project management maturity model on project performance, Unpublished PhD Thesis, , University of Alabama.
Macdonald, R N (2013) A strategy for materials price risk mitigation, Unpublished PhD Thesis, , The University of Alabama.
Mejia Aguilar, G (2013) Improving accuracy of project outcome predictions, Unpublished PhD Thesis, , University of Alabama.
Nguyen, T T (2017) Modeling of clt creep behavior and real-time hybrid simulation of a clt-lifs building, Unpublished PhD Thesis, , The University of Alabama.
Ogunrinde, O (2020) Enhancing quality management in highway construction using emerging methods, Unpublished PhD Thesis, , University of Alabama.
Okpala, I U (2022) Robotics and automation in construction: Developing foundational insight and tools to support safe implementation, Unpublished PhD Thesis, , University of Alabama.
Premraj, P (2017) Assessment of project controls for shutdowns/turnarounds/outages, Unpublished PhD Thesis, , University of Alabama.
Shen, X (2017) Location-based leading indicators in BIM for construction safety, Unpublished PhD Thesis, , University of Alabama.
Song, S (2017) Construction equipment travel path visualization and productivity evaluation, Unpublished PhD Thesis, , University of Alabama.
- Type: Thesis
- Keywords: economic growth; workforce; construction equipment; construction firms; construction project; construction site; equipment; wages; building information model; building information modeling; feedback; laser scanning; productivity; safety; visualization; co
- ISBN/ISSN:
- URL: https://www.proquest.com/docview/2017292537
- Abstract:
The U. S. construction industry represents approximately 4% of the U. S. gross domestic product (BEA 2015) and currently involves over 6 million workers employed by an estimated 750,000 construction firms (BLS 2015). Within this industry, productivity is a key driver for economic growth and strongly affects prosperity for the country (Vogl and Abdel-Wahab 2014). More specifically, higher construction productivity and more reliable installation (quality) translates into higher wages and increased profits (Vogl and Abdel-Wahab 2014). On many construction projects, productivity is defined or greatly impacted by equipment cycle time. Furthermore, the U. S. construction industry continues to be one of the more dangerous work environments for employees (BLS 2015). Construction workers in the U. S. experience a disproportionate number of fatalities when compared other major industrial sectors in the U. S. (BLS 2013). Visibility has proven to be a major cause of accidents on construction sites (Hinze and Teizer 2011). This research seeks to prove the hypothesis that visibility and location-based data can be automatically collected and analyzed for construction equipment operators to assess a construction equipment cycle. As one of the more promising recent implementations in the construction industry, sensing and design technology provide unique opportunities to capture and analyze location-based information on construction sites. These technologies can enable productivity managers to identify, assess, and decrease the overall cycle time of a specific operation. This research implements Building Information Modeling (BIM), Global Positioning System (GPS) location identification, and laser scanning to enable automated data collection and analysis. The overall objective of the research is to automatically capture and analyze elements of a construction equipment cycle. The outcomes of this research addresses the following key components of an equipment cycle time: 1) automated cycle time path planning, 2) location-based data capture and analysis of real-time equipment cycles, and 3) equipment path environment visualization. The research framework was tested with active construction site data, and feedback from the workforce and management was assessed and integrated into the research approach. The research has the potential to improve productivity on construction sites and enhance construction employee safety performance. It will also assist in adding a link between productivity planning and management and existing project BIMs.
Stone, M L C (2013) Development of unit cost estimating models with respect to scale economies and material price volatility for use in probabilistic life cycle cost analyses, Unpublished PhD Thesis, , University of Alabama.
Thomas, W K (2013) The impact of RFP phase project scope development on the successful outcome of construction projects using the design build project delivery method, Unpublished PhD Thesis, , University of Alabama in Huntsville.
Watson, S V (2010) Pre-disaster planning for transportation infrastructure recovery, Unpublished PhD Thesis, , The University of Alabama at Birmingham.